AMIP II Diagnostic Subproject 32

Surface and Atmospheric Radiative Fluxes
Project coordinator:
Martin Wild and Atsumu Ohmura1
Gerald L. Potter and Justin J. Hnilo2

1Swiss Federal Institute of Technology, CH 8057 Zurich, Switzerland
2The Program for Climate Model Diagnosis and Intercomparison

Data Requirements


Radiative processes are of key importance for understanding the genesis and evolution of the global climate system. Due to recent satellite programs such as ERBE (Earth Radiation Budget Experiment), the net exchange of radiative energy between the global climate system and outer space is well established (Barkstrom et al. 1990). Far larger uncertainties still exist in the knowledge on the disposition of this energy within the climate system, such as the partitioning of the energy absorption between the the atmosphere and the surface, and between clouds and the cloud-free atmosphere. Large uncertainties  are therefore also found in the disposition of radiative energy within different General Circulation Models (GCMs) (e.g., Randall et al. 1992, Cess et al. 1995, Wild et al. 1995, Li et al. 1995).

Reliable surface radiation data is essential to determine the absorption of radiative energy at the surface and in the atmosphere. Few studies, however, have attempted to compare the GCM-simulated radiative fluxes directly with surface observations. Attempts to compare climate models using the AMIP I model output have been limited by the data set archived that does not include separated clear and cloudy fluxes (Potter et al. 1996).  The general lack of comprehensive observed surface radiative fluxes has long limited the validation process of GCMs. Recently, the availability and quality of surface radiation observations has been improved with the development of two databases at the applicants' institute, which offer now comprehensive datasets of fully quality checked surface radiation data: The Global Energy Balance Archive (GEBA, World Climate Program -Water Project A7, Ohmura et al. 1989, Gilgen et al. 1997) and the database of the Baseline Surface Radiation Network (Ohmura et al. 1998). GEBA is a database for the worldwide instrumentally-measured energy fluxes at the Earth's surface with currently 250,000 monthly mean data entries for about 1600 sites. This dataset allows an assessment of the calculated flux climatologies on a monthly mean basis at a large number of sites. The database of the Baseline Surface Radiation Network (BSRN) includes only a selected number of sites, but with observations of the highest possible accuracy at high temporal resolution (minute values).

The most extensive use of GEBA for GCM validation was made in the studies of Wild et al .(1995a, 1995b, 1997, 1998a) using various versions of the ECHAM GCM. The investigations showed an overestimation of the GCM-calculated insolation at the surface, due to a lack of short-wave absorption in the atmosphere. Indications for a lack of short-wave absorption were not just found in the all-sky atmosphere, but also in the cloud-free GCM atmospheres (Wild et al. 1995, Wild and Liepert 1998). In the long-wave, on the other hand, evidence for an underestimation in the GCM-calculated downward flux at the surface has been found. Subsets of the data now contained in GEBA have also been used in the works of Garratt (1994), Arking (1996), and Zhang et al. (1998), which indicate similar biases in other GCMs.

The methodology used by the applicants for the validation of the ECHAM GCM has been adopted to other models in the framework of the EU project HIRETYCS (High Resolution Ten Year Climate Simulation), which included the intercomparison and validation of AMIP simulations performed with high resolution versions of the European GCMs and Re-Analysis (Wild 1997, Wild et al. 1998b). After the expertise gained with a small number of GCMs in the above project, the applicants plan to extend their investigations to include state-of-the art versions of all major modeling groups. This would allow for an overview over the ability of the latest generation of GCMs to simulate the radiative fluxes both in the cloudy and cloud-free atmosphere. The context of AMIP II seems the ideal framework for such an endeavor. The time is optimal to perform this task since the implementation of the rigorous quality control procedures in the GEBA has just been completed, thereby ensuring an optimal quality of data which could not been guaranteed in the prior validation studies. Furthermore, the BSRN network is now fully operational, with currently 15 sites reporting their data to the applicants' institute.


The principal aims of this subproject are:
1)      to assess the ability of the GCMs participating in AMIP II to simulate the mean monthly incident short-wave and long-wave radiation at the surface compared to more than 750 observation sites as available from the most recent states of the GEBA and BSRN databases.
2)      to evaluate monthly mean GCM-calculated climatologies of clear-sky short-wave and long-wave surface fluxes at selected sites with measurements of high quality and high temporal resolution  as available from the BSRN database.
3)      to estimate the mean monthly short-wave atmospheric column absorption by combining the surface climatologies used in 1) and 2) with collocated TOA observations from satellite. This allows an assessment of the all-sky short-wave atmospheric absorption in the GCMs above more than 700 sites from GEBA, and both clear-sky and all-sky atmospheric absorption at the BSRN sites.
4)      to assess the model-calculated surface and atmospheric cloud radiative forcing at sites where both clear-sky and all-sky absorption are available (BSRN sites).
5)      to  compare trends and variability in the GCM simulated surface radiative fluxes over the AMIP period with observed statistics in the GEBA data as given in Gilgen et al. (1998).


The GCM radiative fluxes will be assessed in a pointwise comparison between the observed and model-calculated fluxes interpolated to the observation sites, as done in Wild et al. (1995a, 1995b, 1998a). Monthly mean observed downward fluxes of short-wave and long-wave radiation can be readily extracted from the GEBA and BSRN Databases. To assess the clear-sky climatology of surface insolation in the GCMs, the applicants are currently preparing an observational dataset of clear-sky climatologies at selected sites worldwide. The establishment of clear-sky climatologies is only possible at sites with observations of high temporal resolution and additional information on cloudiness to allow for the extraction of clear-sky episodes. The data from the BSRN database are ideal for this task as they are not only measured at very high frequency (minutes values), but also contain extensive additional information on the atmospheric structure above the sites (synop and radiosonde observations). The clear-sky climatologies are then constructed from composites of cloud-free episodes. In a pilot study, observed clear-sky climatologies of surface insolation have been derived for a number of sites in Germany (Wild and Liepert 1998). To obtain a reference dataset for the assessment of the GCM absorbed short-wave radiation at the surface, the observed values of the incoming short-wave radiation are weighted with the collocated values taken from surface albedo climatologies as e.g. provided by the Surface Radiation Budget Project (SRB, Darnell et al. 1992). To determine the total absorbed solar energy in the surface-atmosphere column at the GEBA and BSRN sites, TOA fluxes from satellite observations are used (eg. Barkstrom et al. 1990). Finally, the atmospheric short-wave absorption above the observation sites is determined as residual of the net flux differences at the top of atmosphere and at the surface, respectively, as outlined in Wild et al. (1998a).

Data Requirements

Monthly means of the different components of the surface radiation budget, both for clear-sky and all-sky conditions are required. Of particular interest are the downward components of the radiative fluxes as they can be most directly be compared with surface measurements. For the assessment of the atmospheric absorption, the radiation fluxes at the TOA are additionally required. Data on atmospheric humidity and cloudiness are further desirable for the interpretation of the flux biases.

Thus, from Table 2 we require:
rsds    Surface incident short-wave
rsus    surface reflected short-wave
rsdscs  surface incident clear-sky shor-twave radiation
rsuscs  surface reflected clear-sky short-wave radiation
rlds    surface downwelling long-wave
rldscs  surface downwelling clear-sky long-wave
rlus    surface upwellling long-wave
rlut    outgoing long-wave radiation
rlutcs  TOA clear-sky long-wave radiation
rsdt    TOA incident short-wave radiation
rsut    TOA reflected short-wave radiation
rsutcs  TOA reflected clear-sky short-wave radiation
prw     precipitable water
clt     total cloud cover
clwvi   Vertically integrated cloud water

Arking, A., 1996: Absorption of solar energy in the atmosphere: Discrepancy between model and observations. Science, 273, 779-782.

Barkstrom, B.R., E.F. Harrison, and R.B. Lee III, 1990: Earth Radiation Budget Experiment. EOS, 71, 297-305.

Cess, R. D. and co-authors, 1995, Absorption of solar radiation by clouds: observations versus models. Science, 267, 496-499.

Darnell, W.L., W.F. Staylor, S.K. Gupta, N.A. Ritchey, and A.C. Wilber, 1992: Seasonal variation of surface radiation budget derived from International Satellite Cloud Climatology Project C1 data. J. Geophys. Res., 97, 15741-15760.

Garratt, J. R., 1994: Incoming shortwave fluxes at the surface - a comparison of GCM results with observations. J. Climate, 7, 72-80.

Gilgen, H., M. Wild and A. Ohmura, 1998: Means and trends of shortwave irradiance at the surface estimated from Global Energy Balance Archive data. J. Climate, 11, 2042-2061.

Li, Z, H. W. Barker, and L. Moreau, 1995, The variable effect of clouds on atmospheric absorption of solar radiation. Nature, 376, 486-490.

Ohmura, A., H. Gilgen, and M. Wild, 1989: Global Energy Balance Archive GEBA, World Climate Program - Water Project A7, Report 1: Introduction. Zuercher Geografische Schriften Nr. 34, Verlag der Fachvereine, Zuerich, 62pp.

Ohmura et al., 1998: Baseline Surface Radiation Network (BSRN/WCRP), a new precision radiometry for climate research, Bull. Amer. Meteor. Soc., 79, 2115-2136

Potter, G. L ., M. Fiorino, 1996; AMIP Diagnostic Subproject on Cloud Forcing: Some Preliminary Findings, in: H. LeTreut (ed), Climate Sensitivity to Radiative Perturbations: Physical Mechanisms and Their Validation, NATO ASI Series, Vol. 34, 3-17.

Randall, D. A., and co-authors, 1992: Intercomparison and interpretation of surface energy fluxes in atmospheric general circulation models. J. Geophys. Res., 97, 3711-3725.

Wild,  M., Ohmura A., Gilgen H., Roeckner E., 1995a: Validation of GCM simulated radiative fluxes using surface observations. J. of Climate, 8, 1309-1324.

Wild,  M., Ohmura A., Gilgen H., Roeckner E., 1995b: Regional climate simulation with a high resolution GCM: surface radiative fluxes. Climate Dynamics, 11, 469-486.

Wild,  M., Ohmura A., Cubasch U., 1997: GCM simulated surface energy fluxes in climate change experiments. J. of Climate, 10, 3093-3110.

Wild,  M., 1997: Surface radiative fluxes in high resolution GCMs and Re-analysis. In: Proceedings of the second HIRETYCS meeting, edited by M. Diqui and Alain Braun. Mitiofrance, Toulouse, p. 99-118.

Wild, M., A. Ohmura, H. Gilgen, E. Roeckner, M. Giorgetta, J.J. Morcrette, 1998a: The disposition of radiative energy in the global climate system: GCM versus observational estimates. Climate Dynamics, 14, 853-869.

Wild M., Ohmura A., Gilgen H., and Morcrette J.J., 1998b. The distribution of solar energy at the earth's surface as calculated in the ECMWF Re-analysis. Geophysical Research Letters, 25, 4373-4376.

Wild, M., and B. Liepert, 1998: Excessive transmission of solar radiation through the cloud-free atmosphere, Geophysical Research Letters, 25, 2165-2168.

Zhang, M.H., Lin, W.Y., and Kiehl, J.T., 1998: Bias of atmospheric shortwave absorption in the NCAR community climate models 2 and 3: Comparison with monthly ERBE/GEBA measurements. J. Geophys. Res., 103, 8919-8925.

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